ScholarGate
المساعد

قارن الطرق

راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.

التحليل التلوي الشبكي×الانحدار التلوي×
المجالتجميع الأدلةالتحليل البعدي
العائلةProcess / pipelineRegression model
سنة النشأة20022002
صاحب الطريقةLumley (2002)Simon Thompson & Julian Higgins
النوعMethodWeighted regression for effect-size heterogeneity
المصدر التأسيسيLumley, T. (2002). Network meta-analysis for indirect treatment comparisons. Statistics in Medicine, 21(16), 2313–2324. DOI ↗Thompson, S. G., & Higgins, J. P. T. (2002). How should meta-regression analyses be undertaken and interpreted? Statistics in Medicine, 21(11), 1559–1573. DOI ↗
الأسماء البديلةMixed Treatment Comparison, MTC, Indirect Comparison Meta-AnalysisMeta-Analytic Regression, Weighted Regression in Meta-Analysis, Moderator Analysis, Meta-regresyon
ذات صلة12
الملخصNetwork meta-analysis (NMA) is a systematic method for comparing multiple interventions simultaneously within a single analytical framework, incorporating both direct evidence (head-to-head trials) and indirect evidence (comparisons via common comparators). First formalized by Lumley in 2002, NMA allows researchers to rank treatments and quantify comparative effectiveness even when some treatment pairs have never been directly studied.Meta-regression is a statistical technique that extends conventional meta-analysis by regressing study-level effect sizes on one or more study characteristics (moderators) to explain between-study heterogeneity. Formalized by Thompson and Higgins in 2002, it uses weighted least squares — weighting each study by the inverse of its variance — within a mixed-effects framework, allowing researchers to identify which study features systematically account for variation in observed effects across the literature.
ScholarGateمجموعة البيانات
  1. v1
  2. 3 المصادر
  3. PUBLISHED
  1. v1
  2. 1 المصادر
  3. PUBLISHED

انتقل إلى البحث تنزيل الشرائح

ScholarGateقارن الطرق: Network Meta-Analysis · Meta-Regression. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare